Managing committed processing rates for shared resources

ABSTRACT

Commitments against various resources can be dynamically adjusted for customers in a shared-resource environment. A customer can provision a data volume with a committed rate of Input/Output Operations Per Second (IOPS) and pay only for that commitment (plus any overage), for example, as well as the amount of storage requested. The customer can subsequently adjust the committed rate of IOPS by submitting an appropriate request, or the rate can be adjusted automatically based on any of a number of criteria. Data volumes for the customer can be migrated, split, or combined in order to provide the adjusted rate. The interaction of the customer with the data volume does not need to change, independent of adjustments in rate or changes in the data volume, other than the rate at which requests are processed.

BACKGROUND

As an increasing number of applications and services are being madeavailable over networks such as the Internet, an increasing number ofcontent, application, and/or service providers are turning totechnologies such as remote resource sharing cloud computing. Cloudcomputing, in general, is an approach to providing access to electronicresources through services, such as Web services, where the hardwareand/or software used to support those services is dynamically scalableto meet the needs of the services at any given time. A user or customertypically will rent, lease, or otherwise pay for access to resourcesthrough the cloud, and thus does not have to purchase and maintain thehardware and/or software to provide access to these resources.

In some environments, multiple users can share resources such as datarepositories, wherein the users can concurrently send multiple readand/or write requests to be executed against the same data instance, forexample. Problems can arise, however, when the number of concurrentrequests exceeds the ability of the instance to process those requests.In one example, a data server for an instance might get into an overloadsituation and begin putting back pressure on the incoming requests inorder to reduce the rate of incoming requests and allow the system torecover from the overload situation. As a result of the push back,however, customers might not receive a desired or necessary rate ofrequest handling (e.g., satisfying or otherwise processing receivedrequests), which can upset the customers and in some cases cause thecustomers to look to other providers for data storage and similarresources. Certain conventional approaches attempt to throttle requestswhen a particular customer exceeds some usage threshold, for example,but these approaches tend to be reactive and can still lead to the othercustomers of a resource experiencing slow downs and overload situations.Further, conventional approaches do not provide customers with theability to easily adjust the rates or allocation of various resources.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments in accordance with the present disclosure will bedescribed with reference to the drawings, in which:

FIG. 1 illustrates an environment in which various embodiments can beimplemented;

FIG. 2 illustrates an example separation of management and hostcomponents that can be used in accordance with various embodiments;

FIG. 3 illustrates an example allocation for multiple customers that canbe used in accordance with various embodiments;

FIG. 4 illustrates an example allocation across multiple resourceinstances that can be used in accordance with various embodiments;

FIG. 5 illustrates an example allocation for multiple customers on asingle resource instance that can be used in accordance with variousembodiments;

FIG. 6 illustrates an example allocation for an increased customercommitment using multiple resource instances that can be used inaccordance with various embodiments;

FIG. 7 illustrates an example process for obtaining a guaranteed levelof service in accordance with one embodiment;

FIG. 8 illustrates an example allocation for an increased customercommitment using multiple resource instances that can be used inaccordance with various embodiments;

FIG. 9 illustrates an example allocation for an increased customercommitment including migrating data volumes and splitting acrossmultiple resource instances that can be used in accordance with variousembodiments;

FIG. 10 illustrates an example allocation combining data volumes for acustomer in accordance with one embodiment; and

FIG. 11 illustrates an example environment that can take advantage offunctionality of the various embodiments.

DETAILED DESCRIPTION

Systems and methods in accordance with various embodiments of thepresent disclosure may overcome one or more of the aforementioned andother deficiencies experienced in conventional approaches to managingaspects of resource sharing and allocation in an electronic environment.For example, various embodiments enable users to request a specificquality of service or level of processing, such as a minimum and/orcommitted rate of input/output operations per second (IOPS) against aparticular resource. The requested amount can be any appropriate amount,which can be less than the total amount provided by the respectiveresource, providing a finer granularity than is possible withconventional approaches. Multiple customers can be assigned to a singleresource, such as a data server, with each of the customers potentiallyreceiving a guaranteed level of service. In various embodiments,customers requesting rate commitments that cannot be provided by asingle available resource can have the commitment spread across multipleresources or resource instances. Each resource can have an acceptablelevel of guarantees (e.g., rate commitments), which can be a percentageor portion of the total amount available on the resource, the fullamount available, or in some cases greater than the total amount. Sincecustomers often will not use the entire committed amount (e.g., theguaranteed rate of IOPS), certain resources can have resourcecommitments above 100% of the available capacity. Further, othercustomers can be provisioned on those resources as well. If less thanthe full available capacity of a resource is committed to guaranteeservice levels, the remaining customers can share the un-committedcapacity. When one of the customers with a guarantee is using less thanthe guaranteed amount, the other customers can utilize this unusedcapacity, until such time as the guaranteed customer requests to usethat capacity. Such an approach improves the quality of service fornon-committed customers, while decreasing the cost of providingguaranteed service levels.

Customers in certain embodiments can provision resources in afine-grained manner that matches the customer's specific performancerequirements. If, for example, a customer has a database that requires300 IOPS, the customer can provision a data volume with a committed rateof 300 IOPS and pay only for that commitment, plus the amount of storagerequested. The customer will be able to complete at least 300 IOPS,averaged over some period, for the data volume. If the customer submits500 IOPS on average, the volume may still complete 500 per second overtime if the system is not under pressure; however, the system willdeliver at least the committed 300 over time even when under pressure.

In a conventional system, a customer wanting a certain IOPS ratetypically has to obtain the appropriate number of physical disks and payfor the amount of storage on those disks. For typical workloads, thecustomer then has to overbuy considerably on storage to get the desiredIOPS rate. Using approaches of the various embodiments, customer canobtain a guaranteed quality of service for a shared storage solution, ata level of granularity not possible with conventional systems. The finergranularity can also represent significant cost savings for a customer,as opposed to buying or renting dedicated hardware.

Systems and methods in accordance with various embodiments can alsoautomatically (utilizing algorithms and/or appropriate logic executed byat least one computing device) migrate data volumes, adjust resourcecommitments, and handle other such tasks pertaining to request ratecommitments or other quality of service levels. In some embodiments, acustomer might request a change in commitment level, or the system orservice might determine that a change in commitment level is to beexecuted. In accordance with various embodiments, the capacity ofvarious resources can be determined and the commitment for a customercan be adjusted automatically, without the customer having to adjust orchange any parameters, applications, etc., in order to effect thechange. Data volumes can be migrated, split, combined, or otherwisemanipulated in accordance with various embodiments, depending at leastin part upon the committed rate or change in rate. Changes can bemanaged from a control plane, for example, with appropriate calls beingmade into the data plane.

Systems and methods in accordance with various embodiments are operableto management access to resources such as data storage. In at least someembodiments, these approaches include providing a block data storageservice that uses multiple server storage systems to reliably storeblock data that may be accessed and used over one or more networks byany of various users, applications, processes, and/or services. Users ofthe block data storage service may each create one or more block datastorage volumes that each have a specified amount of block data storagespace, and may initiate use of such a block data storage volume (alsoreferred to as a “volume” herein) by one or more executing programs,with at least some such volumes having copies stored by two or more ofthe multiple server storage systems so as to enhance volume reliabilityand availability to the executing programs. As one example, the multipleserver block data storage systems that store block data may in someembodiments be organized into one or more pools or other groups thateach have multiple physical server storage systems co-located at ageographical location, such as in each of one or more geographicallydistributed data centers, and the program(s) that use a volume stored ona server block data storage system in a data center may execute on oneor more other physical computing systems at that data center.

In addition, in at least some embodiments, applications that access anduse one or more such non-local block data storage volumes over one ormore networks may each have an associated node manager that manages theaccess to those non-local volumes by the program, such as a node managermodule that is provided by the block data storage service and/or thatoperates in conjunction with one or more Block Data Service (BDS) SystemManager modules. For example, a first user who is a customer of theblock data storage service may create a first block data storage volume,and execute one or more program copies on one or more computing nodesthat are instructed to access and use the first volume (e.g., in aserial manner, in a simultaneous or other overlapping manner, etc.).When an application executing on a computing node initiates use of anon-local volume, the application may mount or otherwise be providedwith a logical block data storage device that is local to the computingnode and that represents the non-local volume, such as to allow theexecuting program to interact with the local logical block data storagedevice in the same manner as any other local hard drive or otherphysical block data storage device that is attached to the computingnode (e.g., to perform read and write data access requests, to implementa file system or database or other higher-level data structure on thevolume, etc.). For example, in at least some embodiments, arepresentative logical local block data storage device may be madeavailable to an executing program via use of an appropriate technology,such as GNBD (“Global Network Block Device”) technology. In addition,when an application interacts with the representative local logicalblock data storage device, the associated node manager may manage thoseinteractions by communicating over one or more networks with at leastone of the server block data storage systems that stores a copy of theassociated non-local volume (e.g., in a manner transparent to theexecuting program and/or computing node) so as to perform theinteractions on that stored volume copy on behalf of the executingprogram. Furthermore, in at least some embodiments, at least some of thedescribed techniques for managing access of applications and services tonon-local block data storage volumes are automatically performed byembodiments of a Node Manager module.

In at least some embodiments, block data storage volumes (or portions ofthose volumes) may further be stored on one or more remote archivalstorage systems that are distinct from the server block data storagesystems used to store volume copies. In various embodiments, the one ormore remote archival storage systems may be provided by the block datastorage service (e.g., at a location remote from a data center or othergeographical location that has a pool of co-located server block datastorage systems), or instead may be provided by a remote long-termstorage service and used by the block data storage, and in at least someembodiments the archival storage system may store data in a format otherthan block data (e.g., may store one or more chunks or portions of avolume as distinct objects).

In some embodiments, at least some of the described techniques areperformed on behalf of a program execution service that managesexecution of multiple programs on behalf of multiple users of theprogram execution service. In some embodiments, the program executionservice may have groups of multiple co-located physical host computingsystems, and may execute users' programs on those physical hostcomputing systems, such as under control of a program execution service(“PES”) system manager, as discussed in greater detail below. In suchembodiments, users of the program execution service (e.g., customers ofthe program execution service who pay fees to use the program executionservice) who are also users of the block data storage service mayexecute programs that access and use non-local block data storagevolumes provided via the block data storage service. In otherembodiments, a single organization may provide at least some of bothprogram execution service capabilities and block data storage servicecapabilities (e.g., in an integrated manner, such as part of a singleservice), while in yet other embodiments the block data storage servicemay be provided in environments that do not include a program executionservice (e.g., internally to a business or other organization to supportoperations of the organization).

In addition, the host computing systems on which programs execute mayhave various forms in various embodiments. Multiple such host computingsystems may, for example, be co-located in a physical location (e.g., adata center), and may be managed by multiple node manager modules thatare each associated with a subset of one or more of the host computingsystems. At least some of the host computing systems may each includesufficient computing resources (e.g., volatile memory, CPU cycles orother CPU usage measure, network bandwidth, swap space, etc.) to executemultiple programs simultaneously, and, in at least some embodiments,some or all of the computing systems may each have one or morephysically attached local block data storage devices (e.g., hard disks,tape drives, etc.) that can be used to store local copies of programs tobe executed and/or data used by such programs. Furthermore, at leastsome of the host computing systems in some such embodiments may eachhost multiple virtual machine computing nodes that each may execute oneor more programs on behalf of a distinct user, with each such hostcomputing system having an executing hypervisor or other virtual machinemonitor that manages the virtual machines for that host computingsystem. For host computing systems that execute multiple virtualmachines, the associated node manager module for the host computingsystem may in some embodiments execute on at least one of multiplehosted virtual machines (e.g., as part of or in conjunction with thevirtual machine monitor for the host computing system), while in othersituations a node manager may execute on a physical computing systemdistinct from one or more other host computing systems being managed.

The server block data storage systems on which volumes are stored mayalso have various forms in various embodiments. In at least someembodiments, some or all of the server block data storage systems may bephysical computing systems similar to the host computing systems thatexecute programs, and in some such embodiments may each execute serverstorage system software to assist in the provision and maintenance ofvolumes on those server storage systems. For example, in at least someembodiments, one or more of such server block data storage computingsystems may execute at least part of the BDS System Manager, such as ifone or more BDS System Manager modules are provided in a distributedpeer-to-peer manner by multiple interacting server block data storagecomputing systems. In other embodiments, at least some of the serverblock data storage systems may be network storage devices that may lacksome I/O components and/or other components of physical computingsystems, such as if at least some of the provision and maintenance ofvolumes on those server storage systems is performed by other remotephysical computing systems (e.g., by a BDS System Manager moduleexecuting on one or more other computing systems). In addition, in someembodiments, at least some server block data storage systems eachmaintains multiple local hard disks, and stripes at least some volumesacross a portion of each of some or all of the local hard disks.Furthermore, various types of techniques for creating and using volumesmay be used, including in some embodiments to use LVM (“Logical VolumeManager”) technology.

In at least some embodiments, some or all block data storage volumeseach have copies stored on two or more distinct server block datastorage systems, such as to enhance reliability and availability of thevolumes. By doing so, failure of a single server block data storagesystem may not cause access of executing programs to a volume to belost, as use of that volume by those executing programs may be switchedto another available server block data storage system that has a copy ofthat volume. In such embodiments, consistency may be maintained betweenthe multiple copies of a volume on the multiple server block datastorage systems in various ways. For example, in some embodiments, oneof the server block data storage systems is designated as storing theprimary copy of the volume, and the other one or more server block datastorage systems are designated as storing mirror copies of the volume insuch embodiments, the server block data storage system that has theprimary volume copy (referred to as the “primary server block datastorage system” for the volume) may receive and handle data accessrequests for the volume, and in some such embodiments may further takeaction to maintain the consistency of the other mirror volume copies(e.g., by sending update messages to the other server block data storagesystems that provide the mirror volume copies when data in the primaryvolume copy is modified, such as in a master-slave computingrelationship manner). Various types of volume consistency techniques maybe used, with additional details included below.

In addition to maintaining reliable and available access of executingprograms to block data storage volumes by moving or otherwisereplicating volume copies when server block data storage systems becomeunavailable, the block data storage service may perform other actions inother situations to maintain access of executing programs to block datastorage volumes. For example, if a first executing program unexpectedlybecomes unavailable, in some embodiments the block data storage serviceand/or program execution service may take actions to have a differentsecond executing program (e.g., a second copy of the same program thatis executing on a different host computing system) attach to some or allblock data storage volumes that were in use by the unavailable firstprogram, so that the second program can quickly take over at least someoperations of the unavailable first program. The second program may insome situations be a new program whose execution is initiated by theunavailability of the existing first program, while in other situationsthe second program may already be executing (e.g., if multiple programcopies are concurrently executed to share an overall load of work, suchas multiple Web server programs that receive different incoming clientrequests as mediated by a load balancer, with one of the multipleprogram copies being selected to be the second program; if the secondprogram is a standby copy of the program that is executing to allow a“hot” swap from the existing first program in the event ofunavailability, such as without the standby program copy being activelyused until the unavailability of the existing first program occurs;etc.). In addition, in some embodiments, a second program to which anexisting volume's attachment and ongoing use is switched may be onanother host physical computing system in the same geographical location(e.g., the same data center) as the first program, while in otherembodiments the second program may be at a different geographicallocation (e.g., a different data center, such as in conjunction with acopy of the volume that was previously or concurrently moved to thatother data center and will be used by that second program). Furthermore,in some embodiments, other related actions may be taken to furtherfacilitate the switch to the second program, such as by redirecting somecommunications intended for the unavailable first program to the secondprogram.

As previously noted, in at least some embodiments, some or all blockdata storage volumes each have copies stored on two or more distinctserver block data storage systems at a single geographical location,such as within the same data center in which executing programs willaccess the volume by locating all of the volume copies and executingprograms at the same data center or other geographical location, variousdesired data access characteristics may be maintained (e.g., based onone or more internal networks at that data center or other geographicallocation), such as latency and throughput. For example, in at least someembodiments, the described techniques may provide access to non-localblock data storage that has access characteristics that are similar toor better than access characteristics of local physical block datastorage devices, but with much greater reliability that is similar to orexceeds reliability characteristics of RAID (“Redundant Array ofIndependent (or Inexpensive) Disks”) systems and/or dedicated SANs(“Storage Area Networks”) and at much lower cost. In other embodiments,the primary and mirror copies for at least some volumes may instead bestored in other manners, such as at different geographical locations(e.g., different data centers), such as to further maintain availabilityof a volume even if an entire data center becomes unavailable. Inembodiments in which volume copies may be stored at differentgeographical locations, a user may in some situations request that aparticular program be executed proximate to a particular volume (e.g.,at the same data center at which the primary volume copy is located), orthat a particular volume be located proximate to a particular executingprogram, such as to provide relatively high network bandwidth and lowlatency for communications between the executing program and primaryvolume copy.

Furthermore, access to some or all of the described techniques may insome embodiments be provided in a fee-based or other paid manner to atleast some users. For example, users may pay one-time fees, periodic(e.g., monthly) fees and/or one or more types of usage-based fees to usethe block data storage service to store and access volumes, to use theprogram execution service to execute programs, and/or to use archivalstorage systems (e.g., provided by a remote long-term storage service)to store long-term backups or other snapshot copies of volumes. Fees maybe based on one or more factors and activities, such as indicated in thefollowing non-exclusive list: based on the size of a volume, such as tocreate the volume (e.g., as a one-time fee), to have ongoing storageand/or use of the volume (e.g., a monthly fee), etc.; based on non-sizecharacteristics of a volume, such as a number of mirror copies,characteristics of server block data storage systems (e.g., data accessrates, storage sizes, etc.) on which the primary and/or mirror volumecopies are stored, and/or a manner in which the volume is created (e.g.,a new volume that is empty, a new volume that is a copy of an existingvolume, a new volume that is a copy of a snapshot volume copy, etc.);based on the size of a snapshot volume copy, such as to create thesnapshot volume copy (e.g., as a one-time fee) and/or have ongoingstorage of the volume (e.g., a monthly fee); based on the non-sizecharacteristics of one or more snapshot volume copies, such as a numberof snapshots of a single volume, whether a snapshot copy is incrementalwith respect to one or more prior snapshot copies, etc.; based on usageof a volume, such as the amount of data transferred to and/or from avolume (e.g., to reflect an amount of network bandwidth used), a numberof data access requests sent to a volume, a number of executing programsthat attach to and use a volume (whether sequentially or concurrently),etc.; based on the amount of data transferred to and/or from a snapshot,such as in a manner similar to that for volumes; etc. In addition, theprovided access may have various forms in various embodiments, such as aonetime purchase fee, an ongoing rental fee, and/or based on anotherongoing subscription basis. Furthermore, in at least some embodimentsand situations, a first group of one or more users may provide data toother users on a fee-based basis, such as to charge the other users forreceiving access to current volumes and/or historical snapshot volumecopies created by one or more users of the first group (e.g., byallowing them to make new volumes that are copies of volumes and/or ofsnapshot volume copies; by allowing them to use one or more createdvolumes; etc.), whether as a one-time purchase fee, an ongoing rentalfee, or on another ongoing subscription basis.

In some embodiments, one or more application programming interfaces(APIs) may be provided by the block data storage service, programexecution service and/or remote long-term storage service, such as toallow other programs to programmatically initiate various types ofoperations to be performed (e.g., as directed by users of the otherprograms). Such operations may allow some or all of the previouslydescribed types of functionality to be invoked, and include, but are notlimited to, the following types of operations: to create, delete,attach, detach, or describe volumes; to create, delete, copy or describesnapshots; to specify access rights or other metadata for volumes and/orsnapshots; to manage execution of programs; to provide payment to obtainother types of functionality; to obtain reports and other informationabout use of capabilities of one or more of the services and/or aboutfees paid or owed for such use; etc. The operations provided by the APImay be invoked by, for example, executing programs on host computingsystems of the program execution service and/or by computing systems ofcustomers or other users that are external to the one or moregeographical locations used by the block data storage service and/orprogram execution service.

FIG. 1 illustrates an example network configuration 100 in whichmultiple computing systems are operable to execute various programs,applications, and/or services, and further operable to access reliablenon-local block data storage, such as under the control of a block datastorage service and/or program execution service, in accordance withvarious embodiments. In particular, in this example, a program executionservice manages the execution of programs on various host computingsystems located within a data center 102, and a block data storageservice uses multiple other server block data storage systems at thedata center to provide reliable non-local block data storage to thoseexecuting programs. Multiple remote archival storage systems external tothe data center may also be used to store additional copies of at leastsome portions of at least some block data storage volumes.

In this example, a data center 102 includes a number of racks 104, eachrack including a number of host computing devices 106, as well as anoptional rack support computing system 134 in this example embodiment.The host computing systems 106 on the illustrated rack 104 each host oneor more virtual machines 110 in this example, as well as a distinct NodeManager module 108 associated with the virtual machines on that hostcomputing system to manage those virtual machines. One or more otherhost computing systems 116 may also each host one or more virtualmachines 110 in this example. Each virtual machine 110 may act as anindependent computing node for executing one or more program copies (notshown) for a user (not shown), such as a customer of the programexecution service. In addition, this example data center 102 furtherincludes additional host computing systems 114 that do not includedistinct virtual machines, but may nonetheless each act as a computingnode for one or more programs (not shown) being executed for a user. Inthis example, a Node Manager module 112 executing on a computing system(not shown) distinct from the host computing systems 114 and 116 isassociated with those host computing systems to manage the computingnodes provided by those host computing systems, such as in a mannersimilar to the Node Manager modules 108 for the host computing systems106. The rack support computing system 134 may provide various utilityservices for other computing systems local to its rack 102 (e.g.,long-term program storage, metering, and other monitoring of programexecution and/or of non-local block data storage access performed byother computing systems local to the rack, etc.), as well as possibly toother computing systems located in the data center. Each computingsystem may also have one or more local attached storage devices (notshown), such as to store local copies of programs and/or data created byor otherwise used by the executing programs, as well as various othercomponents.

In this example, an optional computing system 118 is also illustratedthat executes a PES System Manager module for the program executionservice to assist in managing the execution of programs on the computingnodes provided by the host computing systems located within the datacenter (or optionally on computing systems located in one or more otherdata centers 128, or other remote computing systems 132 external to thedata center). As discussed in greater detail elsewhere, a PES SystemManager module may provide a variety of services in addition to managingexecution of programs, including the management of user accounts (e.g.,creation, deletion, billing, etc.); the registration, storage, anddistribution of programs to be executed; the collection and processingof performance and auditing data related to the execution of programs;the obtaining of payment from customers or other users for the executionof programs; etc. In some embodiments, the PES System Manager module maycoordinate with the Node Manager modules 108 and 112 to manage programexecution on computing nodes associated with the Node Manager modules,while in other embodiments the Node Manager modules may not assist inmanaging such execution of programs.

This example the data center 102 also includes a computing system 124that executes a Block Data Storage (“BDS”) system manager module for theblock data storage service to assist in managing the availability ofnon-local block data storage to programs executing on computing nodesprovided by the host computing systems located within the data center(or optionally on computing systems located in one or more other datacenters 128, or other remote computing systems 132 external to the datacenter). In particular, in this example, the data center 102 includes apool of multiple server block data storage systems 122, which each havelocal block storage for use in storing one or more volume copies 120.Access to the volume copies 120 is provided over the internal network(s)126 to programs executing on various computing nodes 110 and 114. Asdiscussed in greater detail elsewhere, a BDS System Manager module mayprovide a variety of services related to providing non-local block datastorage functionality, including the management of user accounts (e.g.,creation, deletion, billing, etc.); the creation, use and deletion ofblock data storage volumes and snapshot copies of those volumes; thecollection and processing of performance and auditing data related tothe use of block data storage volumes and snapshot copies of thosevolumes; the obtaining of payment from customers or other users for theuse of block data storage volumes and snapshot copies of those volumes;etc. In some embodiments, the BDS System Manager module may coordinatewith the Node Manager modules to manage use of volumes by programsexecuting on associated computing nodes, while in other embodiments theNode Manager modules may not be used to manage such volume use. Inaddition, in other embodiments, one or more BDS System Manager modulesmay be structured in other manners, such as to have multiple instancesof the BDS System Manager executing in a single data center (e.g., toshare the management of non-local block data storage by programsexecuting on the computing nodes provided by the host computing systemslocated within the data center), and/or such as to have at least some ofthe functionality of a BDS System Manager module being provided in adistributed manner by software executing on some or all of the serverblock data storage systems 122 (e.g., in a Peer to-peer manner, withoutany separate centralized BDS System Manager module on a computing system124).

In this example, the various host computing systems, server block datastorage systems, and computing systems are interconnected via one ormore internal networks 126 of the data center, which may include variousnetworking devices (e.g., routers, switches, gateways, etc.) that arenot shown. In addition, the internal networks 126 are connected to anexternal network 130 (e.g., the Internet or other public network) inthis example, and the data center 102 may further include one or moreoptional devices (not shown) at the interconnect between the data centerand an external network (e.g., network proxies, load balancers, networkaddress translation devices, etc.). In this example, the data center 102is connected via the external network 130 to one or more other datacenters 128 that each may include some or all of the computing systemsand storage systems illustrated with respect to data center 102, as wellas other remote computing systems 132 external to the data center. Theother computing systems 132 may be operated by various parties forvarious purposes, such as by the operator of the data center or thirdparties (e.g., customers of the program execution service and/or of theblock data storage service). In addition, one or more of the othercomputing systems may be archival storage systems (e.g., as part of aremote network-accessible storage service) with which the block datastorage service may interact, such as under control of one or morearchival manager modules (not shown) that execute on the one or moreother computing systems or instead on one or more computing systems ofthe data center, as described in greater detail elsewhere. Furthermore,while not illustrated here, in at least some embodiments, at least someof the server block data storage systems 122 may further beinterconnected with one or more other networks or other connectionmediums, such as a high-bandwidth connection over which the serverstorage systems 122 may share volume data (e.g., for purposes ofreplicating copies of volumes and/or maintaining consistency betweenprimary and mirror copies of volumes), with such a high-bandwidthconnection not being available to the various host computing systems inat least some such embodiments.

It will be appreciated that the example of FIG. 1 has been simplifiedfor the purposes of explanation, and that the number and organization ofhost computing systems, server block data storage systems and otherdevices may be much larger than what is depicted in FIG. 1. For example,as one illustrative embodiment, there may be approximately 4,000computing systems per data center, with at least some of those computingsystems being host computing systems that may each host fifteen virtualmachines, and/or with some of those computing systems being server blockdata storage systems that may each store several volume copies. If eachhosted virtual machine executes one program, then such a data center mayexecute as many as sixty thousand program copies at one time.Furthermore, hundreds or thousands (or more) volumes may be stored onthe server block data storage systems, depending on the number of serverstorage systems, size of the volumes, and number of mirror copies pervolume. It will be appreciated that in other embodiments, other numbersof computing systems, programs and volumes may be used.

FIG. 2 illustrates an example environment 200 including computingsystems suitable for managing the provision and use of reliablenon-local block data storage functionality to clients that can be usedin accordance with various embodiments. In this example, a managementsystem 202, such as one or more server computers including one or moreexternally-facing customer interfaces, is programmed to execute anembodiment of at least one BDS System Manager module 204 to manageprovisioning of non-local block data storage functionality to programsexecuting on host computing systems 208 and/or on at least some othercomputing systems 218, such as to block data storage volumes (not shown)provided by the server block data storage systems 220. Each of the hostcomputing systems 208 in this example also executes an embodiment of aNode Manager module 210 to manage access of programs 214 executing onthe host computing system to at least some of the non-local block datastorage volumes, such as in a coordinated manner with the BDS SystemManager module 204 over a network 216 (e.g., an internal network of adata center, not shown, that includes the computing systems 202, 208,220, and optionally at least some of the other computing systems 218).In other embodiments, some or all of the Node Manager modules 210 mayinstead manage one or more other computing systems (e.g., the othercomputing systems 218).

In addition, multiple server block data storage systems 220 areillustrated that each can store at least some of the non-local blockdata storage volumes (not shown) used by the executing programs 214,with access to those volumes also provided over the network 216 in thisexample. One or more of the server block data storage systems 220 mayalso each store a server software component (not shown) that managesoperation of one or more of the server block data storage systems, aswell as various information (not shown) about the data that is stored bythe server block data storage systems. Thus, in at least someembodiments, the server computing system 202 of FIG. 2 may correspond tothe computing system 124 of FIG. 1, one or more of the Node Managermodules 108 and 112 of FIG. 1 may correspond to the Node Manager modules210 of FIG. 2, and/or one or more of the server block data storagecomputing systems 220 of FIG. 2 may correspond to server block datastorage systems 122 of FIG. 1. In addition, in this example embodiment,multiple archival storage systems 222 are illustrated, which may storesnapshot copies and/or other copies of at least portions of at leastsome block data storage volumes stored on the server block data storagesystems 220. The archival storage systems 222 may also interact withsome or all of the computing systems 202, 208, and 220, and in someembodiments may be remote archival storage systems (e.g., of a remotestorage service, not shown) that interact with the computing systemsover one or more other external networks (not shown).

The other computing systems 218 may further include other proximate orremote computing systems of various types in at least some embodiments,including computing systems via which customers or other users of theblock data storage service interact with the management and/or hostsystems. Furthermore, one or more of the other computing systems 218 mayfurther execute a PES System Manager module to coordinate execution ofprograms on the host computing systems 208 and/or other host computingsystems 218, or the management system 202 or one of the otherillustrated computing systems may instead execute such a PES SystemManager module, although a PES System Manager module is not illustratedin this example.

In the illustrated embodiment, a Node Manager module 210 is executing inmemory in order to manage one or more other programs 214 executing inmemory on the computing system, such as on behalf of customers of theprogram execution service and/or block data storage service. In someembodiments, some or all of the computing systems 208 may host multiplevirtual machines, and if so, each of the executing programs 214 may bean entire virtual machine image (e.g., with an operating system and oneor more application programs) executing on a distinct hosted virtualmachine computing node. The Node Manager module 210 may similarly beexecuting on another hosted virtual machine, such as a privilegedvirtual machine monitor that manages the other hosted virtual machines.In other embodiments, the executing program copies 214 and the NodeManager module 210 may execute as distinct processes on a singleoperating system (not shown) executed on a single computing system 208.

The archival storage system 222 is operable to execute at least oneArchival Manager module 224 in order to manage operation of one or moreof the archival storage systems, such as on behalf of customers of theblock data storage service and/or of a distinct storage service thatprovides the archival storage systems. In other embodiments, theArchival Manager module(s) 224 may instead be executing on anothercomputing system, such as one of the other computing systems 218 or onthe management system 202 in conjunction with the BDS System Managermodule 204. In addition, while not illustrated here, in some embodimentsvarious information about the data that is stored by the archivalstorage systems 222 may be maintained in storage for the archivalstorage systems or elsewhere.

The BDS System Manager module 204 and Node Manager modules 210 may takevarious actions to manage the provisioning and/or use of reliablenon-local block data storage functionality to clients (e.g., executingprograms), as described in greater detail elsewhere. In this example,the BDS System Manager module 204 may maintain a database 206 thatincludes information about volumes stored on the server block datastorage systems 220 and/or on the archival storage systems 222 (e.g.,for use in managing the volumes), and may further store various otherinformation (not shown) about users or other aspects of the block datastorage service. In other embodiments, information about volumes may bestored in other manners, such as in a distributed manner by Node Managermodules 210 on their computing systems and/or by other computingsystems. In addition, in this example, each Node Manager module 210 on ahost computing system 208 may store information 212 about the currentvolumes attached to the host computing system and used by the executingprograms 214 on the host computing system, such as to coordinateinteractions with the server block data storage systems 220 that providethe primary copies of the volumes, and to determine how to switch to amirror copy of a volume if the primary volume copy becomes unavailable.While not illustrated here, each host computing system may furtherinclude a distinct logical local block data storage device interface foreach volume attached to the host computing system and used by a programexecuting on the computing system, which may further appear to theexecuting programs as being indistinguishable from one or more otherlocal physically attached storage devices that provide local storage.

An environment such as that illustrated with respect to FIGS. 1-2 can beused to provide and manage resources shared among various customers. Inone embodiment, a virtualized storage system can be provided using anumber of data servers, each having a number of storage devices (e.g.,storage disks) attached thereto. The storage system can expose thestorage to the customers as a Web service, for example. Customers thencan submit Web services requests, or other appropriate requests orcalls, to allocate storage on those servers and/or access that storagefrom the instances provisioned for those customers. In certainembodiments, a user is able to access the data volumes of these storagedevices as if those storage devices are conventional block devices.Since the data volumes will appear to the customer instances as if eachvolume is a disk drive or similar block device, the volumes can beaddressed with offsets, lengths, and other such conventional blockdevice aspects. Further, such a system can provide what will be referredto herein as “read after write” consistency, wherein data is guaranteedto be able to be read from the data as soon as the data is written toone of these data volumes. Such a system can provide relatively lowlatency, such as latencies less than about ten milliseconds. Such asystem thus in many ways functions as a traditional storage area network(SAN), but with improved performance and scalability.

Using a management system as illustrated in FIG. 2, for example, acustomer can make a Web service call into an appropriate API of a Webservice layer of the system to provision a data volume and attach thatvolume to a data instance for that customer. The management system canbe thought of as residing in a control plane, or control environment,with the data volumes and block storage devices residing in a separatedata plane, or data environment. In one example, a customer with atleast one provisioned instance can call a “CreateVolume” or similar API,via Web services, which enables the customer to specify the amountallows them to specify the amount of storage to be allocated, such as avalue between 1 GB and 1 TB, in 1 GB increments. Components of thecontrol plane, such as a BDS system manager module, can call into thedata plane to allocate the desired amount of storage from the availableresources, and can provide the customer with an identifier for the datavolume. In some embodiments, the customer then can call an“AttachVolume” or similar API, wherein the customer provides values forparameters such as an instance identifier, a volume identifier, and adevice name, depending on factors such as the operating system of theinstance, using a scheme that the operating system provides for harddrives and similar storage devices, as from inside the instance there isno apparent difference, from at least a functionality and naming pointof view, from a physical hard drive. Once the customer has attached thedata volume to a provisioned instance, the customer can perform variousfunctionality, such as to build a file system, use as raw storage for adata system, or any other such activity that would normally be performedwith a conventional storage device. When the customer no longer requiresthe data volume, or for any other appropriate reason, the customer cancall a “DetatchVolume” or similar API, which can cause the associationof the instance to that volume to be removed. In some embodiments, thecustomer can then attach a new instance or perform any of a number ofother such activities. Since the data volume will fail independently ofthe instances in some embodiments, the customer can attach a volume to anew instance if a currently associated instance fails.

In certain approaches, a customer requesting a data volume is not ableto select or request a particular type of volume, or a particular typeof performance. A customer is typically granted an amount of storage,and the performance follows a “best effort” type of approach, whereincustomer requests are performed based on the capability, load, and othersuch factors of the system at the time of the request. Each customer istypically charged the same amount per unit measure, such as the samedollar amount per gigabyte of storage per month, as well as the sameamount per number of I/O requests per month, charged in an amount suchas in increments of millions of requests per month.

As discussed above, however, such an approach can be problematic insituations such as where the number of requests waiting to be processedby an instance exceeds the ability of the instance to process thoserequests. Even if a customer is within the expected or allocated numberof requests for that customer, other customers submitting requests tothat instance can exceed their allocation, creating an overloadsituation where the data server for the instance can begin putting backpressure on the incoming requests in order to reduce the rate ofincoming requests and allow the system to move out of the overloadsituation. Thus, each customer on the device with pending requests canexperience a decrease in the rate of request handling (the “requestrate”), as well as other issues such as a decrease in available storage.

Systems and methods in accordance with various embodiments enablecustomers to ensure a minimum level of performance by enabling eachcustomer to specify one or more committed request rates or otherperformance guarantees. In addition to a minimum amount of storage, eachcustomer can purchase a committed rate of operations, such as a specificnumber of input/output (I/O) operations per second (IOPS). In previoussystems, performance guarantees were obtained by dedicating an entiremachine to a customer, along with dedicated bandwidth, etc., which oftenis overkill. Embodiments discussed herein can allow customers topurchase performance guarantees at any appropriate level of granularity.By managing the performance allocations for customers on variousresources, systems and methods in accordance with various embodimentscan enable customers to purchase volumes that have an IOPS guarantee atany appropriate level, such as between 1 IOPS and 5,000 IOPS. Byallocating portions of disks, spindles, and other such resources, asystem can offer customers guaranteed levels of storage and/or IOPS.

Systems and methods in accordance with various embodiments allow usersto share resources, providing specific guarantees or commitments withrespect to those resources at a level of granularity that is notpossible with conventional solutions. In many cases, customers may wishto specify a minimum processing rate, such as a minimum number of I/Ooperations per second (IOPS). Approaches in accordance with variousembodiments can commit the desired amount of server and other resourcesnecessary to provide at least a committed level of performance. Bycommitting to a level of performance, a customer can receive aconsistent quality of service level that is not affected by theperformance of other customers sharing a device or resource. Even in anoverload situation, the customer can receive at least the guaranteedlevel of service. The amount of guaranteed service can depend uponvarious factors, as well as the amount specified and paid for by thecustomer.

For example, FIG. 3 illustrates an example distribution 300 wherein theprocessing capacity of a server 302 is allocated among severalcustomers. In this example, the server is determined to have a capacityfor about 500 IOPS. This value can be an estimated or average value, andcan be determined or adjusted over time based on monitored performanceor other such information. While all 500 IOPS can be allocated in someembodiments, it can be desirable in other embodiments to only allocate athreshold amount, percentage, or other portion of the total capacity asguarantees. Since the processing time for each request can vary, thenumber of IOPS at any given time can vary as well, such that allocatingall 500 IOPS might cause short periods of time where the customers areunable to receive their guarantees when the actual performance is on theorder of 450 IOPS due to the nature of the requests being processed,etc.

In this example, the system might be able to allocate up to 400 of the500 IOPS available for the server 302. As can be seen, Customer A hasbeen allocated a committed 200 IOPS, Customer B has been allocated acommitted 100 IOPS, and Customer C has been allocated a committed 55IOPS. The remaining customers on the server then can utilize a “bestperformance” or similar approach sharing the remaining 145 IOPS (onaverage). The number of customers sharing the remaining IOPS can beselected or limited based upon a number of factors, such that theremaining customers can still obtain a desirable level of performance alarge percentage of the time.

In many cases, however, Customers A, B, and C will not all utilize theirentire committed capacity. Each of those customers might pay toguarantee a level of performance such that the level is available whenneeded, but often will not actually be running near that peak capacity.In this situation, the remaining Customers D-Z can actually share morethan the remaining 145 IOPS, as those customers can utilize availablecapacity from the committed IOPS that are not being currently used. Thisprovides another advantage, as customers can receive guaranteed levelsof performance, but when those levels are not being fully utilized theremaining capacity can be used to service other customer requests. Suchan approach enables the regular customers (without guarantees) toreceive improved performance, without the need for the provider topurchase excess capacity or provide capacity that is not being utilizeda vast majority of the time.

In some embodiments, any of Customers A-C can exceed their performanceguarantees. For example, Customer A might, for a period of time, submitrequests on the order of 250 IOPS. For the 50 IOPS above the committedrate, those requests in some embodiments can be treated as normalrequests and processed at the same performance level as those ofcustomers D-Z. In an overload situation, any throttling, slow down, orother reduction in processing can then be applied to the 145 or so IOPSthat are not subject to guarantees. The guaranteed levels for CustomersA, B, and C will not be affected, as the overflow adjustments are madeto the non-committed portion. Accordingly, customers with non-guaranteedlevels of service can be charged lower prices per request, period, etc.

In other embodiments, when any of Customers A-C exceed its performanceguarantees, that customer can receive a “blended” or other level ofservice. In a situation where each request for a customer is treatedindividually or without context, such that any single request over acommitted rate can be treated as a request without a committed rate,there can be a negative impact on the other requests for that customer.For example, if Customer A has a committed rate of 250 IOPS and at onepoint issues 251 requests in a second, that single request over the ratecommitment can be processed much more slowly than the other requests,such as at 20 ms instead of 1 ms. If the customer application isexpecting a performance level of about 1 ms and experiences a slowdownwith respect to one request, that can have an impact on the processingof the other requests as well, and can cause a significant slowdown orother problems for the application even though the customer onlyslightly exceeded the threshold for a short period of time.

Systems and methods in accordance with various embodiments address sucha situation by providing a “boost” or blended rate to customers withrate guarantees who exceed those guarantees, which provides a level ofservice between a committed and uncommitted rate. For example, acustomer with a rate guarantee might have any excess requests placed ator near the front of the “queue” for uncommitted requests. In otherembodiments, the customer might receive a lower rate commitment forthose requests, such as might experience a delay of about 5 ms, whichare not processed at the same rate as requests within the committedrate, but are processed more quickly than for customers without acommitted rate. The amount of delay can be related in some embodimentsto the amount of overage and the length of time that the customer isover the guaranteed rate, to provide a relatively uniform degradation inperformance that is at least somewhat proportional to the amount ofoverage. For example, a customer with a guaranteed rate of 100 IOPS whois consistently sending requests at a rate of 500 per second wouldlikely not receive as much of a boost as a customer with a 250 IOPSguaranteed rate who occasionally goes over by a handful of requests. Insome embodiments, a customer can be provided with the same rate for anyoverage, but can be charged a premium for each such request. Many othervariations are possible as well within the scope of the variousembodiments.

To manage the commitments, components of a control plane can essentiallymake reservations against specific servers or other resources in thedata plane. In FIG. 3 where three customers want a total of 355 IOPScommitted, the control plane can reserve that level against a singleserver, for example, and allocate the remainder to any other customerprovisioned on that server. The control plane can also ensure that morevolumes are not allocated to a server than the server can handle, due tospace limitations, the number of I/Os that need to be generated, or anyother such factor.

In some cases, a customer might want a guaranteed level of service thatexceeds the “committable” capacity for a given resource. For example, inFIG. 3 it was stated that the server could allocate 400 IOPS, but 355are already allocated to Customers A-C. If another customer wants 300IOPS, that number would exceed the allowed amount (as well as theaverage capacity) of the server. Thus, the customer cannot receive thedesired commitment on that server. Using the management components ofthe control plane, however, the commitment rate can be allocated acrossmultiple servers. For example, in the allocation 400 of FIG. 4, it isshown that Customer A sends a request from a user device 402 requestinga guarantee of 300 IOPS. The control plane in some embodiments cansearch the available servers to determine if a server is available with300 IOPS left for guarantees. If not, the control plane can attempt tospread the IOPS across as few servers as possible. In this case, thecontrol plane determines to allocate the IOPS guarantee across threeservers, with a first server 404 providing a guarantee of 100 IOPS, asecond server 406 providing a guarantee of 125 IOPS, and a third server408 providing a guarantee of 75 IOPS. Thus, a volume does not need to beresident on a single server as in many conventional systems, but can bepartitioned across multiple servers. The allocation across multipleservers also enables customers to utilize larger data volumes, such asvolumes of 50 terabytes instead of 1 terabyte, as the data can be spreadacross multiple servers. In such an embodiment, a customer can purchasebetween 1 GB and 50 TB of storage, for example, with a desiredcommitment rate, such as a rate between 0 IOPS and 5,000 IOPS. Based onone or more of these values selected by a customer, the control planecan determine an appropriate, if not optimal, way to provide thoseguarantees using available resources in the data plane.

In some embodiments, the committed rate might be allocated up to 100% ofthe capacity of a server. An amount of un-committed usage can bepredicted and/or monitored, such that a number of customers can beallocated to resources that are fully committed, as long as the customeris willing to take resources only as they come available. Certaincustomers might not care when IOPS occur, particularly for certainwrites, such that they would be willing to pay a lower rate to utilizeresources that are guaranteed up to 100%, knowing that some customerslikely will not utilize their full guaranteed levels. Such an approachassists the provider in maximizing the utilization of each resource byallocating un-commited IOPS on resources that are otherwise “fully”committed.

Further, different types of customers will have different requirements.For example, if a disk has 100 TB of space and 100 IOPS capacity, afirst customer might want to store 90 TB of vacation photos that arerarely accessed. That customer might be interested in purchasing 90 TBof storage space along with an uncommitted level of IOPS. Another usermight want a 1 TB database that is going to be under constant use, suchthat the user might want about 100 IOPS. In this example, the firstcustomer could be sold 90% of the for storage, and the other customercan be allocated 90% (or more) of the IOPS of the disk as a commitment.Due to the nature of the customers, they both could be provisioned onthe same disk, where otherwise each might have required a dedicateddisk.

Enabling others to utilize the unused portion of a customer's committedallocation can benefit that customer as well, because the customer maynot have to pay for the entire allocation and thus can receive a lowercost that would be required for a dedicated resource. Further, thecustomer will still receive the guaranteed level of service. When thecustomer is at the full committed level, other customers on that devicewill have to reduce their rate of request or wait longer per request. Insome embodiments, a resource can be fully committed and other users canstill be provisioned on the device to utilize the unused portions of theresource. In some cases, where predictions and monitoring accuratelysupport such use, a resource can even be committed for over 100%, wherethe actual use by the allocated customers will almost never equal orsurpass 100% usage. In such an embodiment, there can be other resourcesthat can pick up any overage in the event of an unlikely event where theresource is overloaded.

In order to make commitments on a new resource (or new instance of aresource), certain default information can be used to make commitments.It can be desirable to use relatively conservative numbers as thedefaults, in order to prevent over-committing a resource. For example, acontrol plane component can use general default information that eachspindle of a particular type can handle 100-120 IOPS. If there aretwelve spindles per server, there can be about 1200-1440 IOPS availableper server. The control plane components can be conservative, initially,and can allocate a first amount, such as up to 400 IOPS, until moreinformation is gained about the performance and usage of that resource.In certain examples customer utilization is about 10%, such that in manyinstances customers are using only 10% of the available IOPS. Thus,dedicating 40% to guaranteed IOPS would still be four times more than isactually being used, and thus likely is still a conservative number.Each server in the data plane can track the amount of available space onthe server, and can store the number of IOPS that are committed for thatserver. Thus, when a new volume is to be created, the control planecomponents can determine a server that, out of that 400 IOPS, has enoughcapacity available that the server is willing to commit for that volume.An approach in one embodiment is to ask servers, at random or in aparticular order, whether they can take a specific number of IOPS, andthis continues until a server is located that can accept the IOPS. Whenthe information is also stored in the control plane, however, thecontrol plane can select an appropriate server first and then contactthat server to take the volume.

In some cases, a customer having a committed IOPS rate, or otherresource commitment, might want or need to adjust that rate. Forexample, a customer application might support additional users oradditional functionality might be pushed out onto the cloud. In anotherexample, a customer might want to reduce the number of committed IOPSwhen the customer is no longer in need of the currently committedcapacity. In yet other examples, a customer might want higher committedrates during periods of peak use, but lower committed rates at all othertimes. Various other situations can arise as well, where a customer maydesire a change in the committed rate.

As discussed, many conventional systems would require a user wanting agreater committed rate to purchase or otherwise obtain additionalhardware, which often is not cost effective for the user and can take asignificant amount of time to obtain, install, and/or activate.Similarly, users wanting a lower commitment would often be stuck withthe hardware already purchased, or left to attempt to resell thehardware to attempt to recoup some of the expenditure.

Systems and methods in accordance with various embodiments enable ratecommitments to be adjusted dynamically, in response to customerrequests, established thresholds, usage variations, or any of a numberof other such criteria or inputs. The system can automatically adjustresources as needed, such as to provision or allocate additionalresources, add or move data volumes, split customers across multipleresources, or any of a number of other such actions as described andsuggested herein. The system in various embodiments includes at leastone monitoring component operable to monitor usage of resources in adata environment and adjust the utilization of the resources based onestablished criteria. The control plane also can include one or moreinterfaces (e.g., Web service APIs) enabling customers to requestspecific changes, or establish criteria to be used in making suchchanges. Various other approaches can be used as well within the scopeof the various embodiments.

FIG. 5 illustrates an example situation 500 wherein each of fourdifferent customers has a rate guaranteed against a common server 502.In this example, the server has a (committable) rate capacity of 400IOPS, and each customer has a committed rate of 100 IOPS. As discussedabove, many customers do not utilize their entire committed allocationsuch that the entire capacity of the server can be committed in variousembodiments, as any overage by one or more of those customers can likelybe processed using the unused capacity committed to one or more of theother users.

In certain instances, however, it can be desirable to adjust the way inwhich the rate commitment is provided for at least one of the customersutilizing that server. If one of the customers needs a higher ratecommitment in this for example, there would not be sufficientcommittable capacity on the server to accommodate the higher rate. Insuch a situation, the data volume for which the additional ratecommitment is needed can be automatically migrated to another serverwithout any knowledge or actions required on the part of the customer.

In a first example 600, as illustrated in FIG. 6, Customer A from FIG. 5is to receive an IOPS rate commitment increase from 100 IOPS to 200IOPS. As can be seen, the full committable capacity of the currentserver instance 502 is already allocated, such that the server cannotprovide the additional commitment for Customer A. In this embodiment,the system (or service) locates a resource instance 602 with thenecessary available capacity to provide the entire rate commitment forCustomer A. Thus, a process or workflow of a management system (oranother such component or process) can migrate the data volume and causethe customer I/O requests to be directed to, and handled by, the secondserver instance 602 without any change necessary to the correspondingclient application, etc. The management process can cause anyappropriate actions to be performed, such as to provision a new datainstance and/or move customer data, update address mapping in the dataplane, etc., such that the customer can receive the higher commitmentrate without any actions or changes needed to be taken on the part ofthe customer.

Using components such as those discussed above, FIG. 7 illustrates anexample process 700 by which a guaranteed level of service, or committedrate of processing, for a resource can be updated for a given customerin accordance with various embodiments. As should be understood, theillustrated steps are examples, and that additional, fewer, oralternative steps can be performed in similar or alternative orders, orin parallel, within the scope of the various embodiments. Further, theprocess can be performed for any appropriate components or elements,such as at least one data instance, repository, or other such datasource in a data environment, here a data plane, using a control planeor a similar data control application or service. While the term“customer” is used herein to refer to the “owner” of specific data, or adata store or instance hosted by the system, it should be understoodthat the term customer is used merely for convenience, and that anyappropriate user or developer can be allowed to access the control planeand data plane in the various embodiments.

In an embodiment where the rate change is triggered by a user request, aWeb services call or similar request is received through one of aplurality of APIs or other such customer-facing interface components702. The request can be analyzed to determine any actions needed toprocess the request, where necessary. As discussed, this can take theform of a component of a Web services layer parsing the request todetermine the action(s) being requested. In an embodiment where the APIreceiving the request corresponds to a specific action to be performed,the Web services layer can extract information from the request to beused in determining aspects or parameters of the action to be performed.

Once one or more requested (or necessary) actions are determined, thesystem can determine the resource(s) (e.g., servers) that the customeris currently using 704, as well as the additional committable capacityof the resource(s) 706. As discussed, in some embodiments this includessearching against a table in a data store accessible to the managementsystem, or other such repository, to determine whether a resource hasthe desired capacity. In other embodiments, this can involve contactingthe servers individually. Even though capacity can be provided bymultiple resource instances, it can be desirable from at least amanagement standpoint to attempt to provide the additional ratecommitment using a resource that the customer is already using, insteadof spreading the customer requests across another resource. If thecurrent resources(s) being used by that customer have the additionalcommittable capacity to satisfy the request 708, the process can causethe resource(s) to allocate the additional commitment 710, whereby theadditional rate can be available immediately to the customer.Information for the change in commitment can be stored to a tableaccessible to the management system 718.

If there is not sufficient committable capacity on the resourcesallocated to the customer, the process can attempt to locate at leastone resource with capacity to satisfy the new rate request 712. In someembodiments, if a single resource instance is available that is able toprovide the desired capacity, the customer allocation can be transferredto that single resource instance instead of being spread across multipleinstances. In other embodiments, additional capacity can be provided byadding the additional capacity of another available resource instance.In some embodiments, the system can attempt to consolidate theallocation for a customer where possible, to minimize or at least reducethe number of instances allocated to a single customer. Various otherapproaches can be used as well within the scope of the variousembodiments.

When at least one additional resource instance is located that is ableto provide the additional commitment, the process can cause theresource(s) to allocate the additional commitment 714. Mappinginformation for the additional resource(s) is generated in order toproperly direct requests for the customer 716. Information for thechange in commitment can be stored to a table or repository accessibleto the management system 718. After the commitment is applied and anynecessary configuration or provisioning actions performed, the customeris able to directly access the resource for which the guarantee wasapplied, and subsequent requests can be processed using the increasedcommitment 720. As mentioned, the user can provided with a DNS addressand port number, for example, such that if the action resulted inmovement of data or another similar action, the customer or anapplication can continue to use the same DNS address, which will bedirected to the appropriate location.

In some embodiments, the customer might not be allocated to a singleresource instance. For example, there might not be a single instancewith sufficient capacity to fill the entire commitment. In other cases,the system might be configured to add the additional capacity using asingle resource, if possible, while leaving the existing customerallocation on the current resources, thereby minimizing volume changes,etc. In other embodiments, the system might prefer to fill the capacityof existing resource instances before allocating additional resources.

FIG. 8 illustrates an example 800 wherein the full commitment is notprovided by a single resource instance, for any of the above or otherappropriate reasons. Again, using the initial example allocation of FIG.5 as a starting point, in this example the original 100 IOPS forCustomer A are still provided by Server X 502. For the additional 100IOPS, however, the additional requests are allocated to a second server,Server Y 802. In this example, the second server instance handlesrequests for other customers, but has sufficient available andcommittable capacity to handle the additional allocation for Customer A.As discussed above, in some embodiments the second server instance couldbe selected by analyzing data stored in a data store of the controlplane to locate an appropriate server to provide the additionalcommitted rate. In other embodiments, servers might be contactedindividually until a server is found that can at least accept theadditional resource commitment for the customer.

In some cases, the requested commitment increase cannot be provided by asingle resource instance. For example, continuing with the initialstarting point of FIG. 5, each server might only be able to commit 400IOPS. If Customer A wants to increase from 100 IOPS to 600 IOPS, thecommitted rate will be unable to be provided by a single resource. Thus,at least two additional resource instances would be needed if theoriginal 100 IOPS are to continue to be provided by the first serverinstance 502. In some embodiments, however, it is desirable to partitionor allocate a customer across as few resources as possible, for reasonssuch as to reduce management complexity and mapping, etc. FIG. 9illustrates an example allocation 900 wherein the requests for CustomerA are removed from Server X 502, the data volume is migrated and split,and the full committed rate is assigned across two resource instances.Here, 400 IOPS are assigned to Server Y 902, with 200 TOPS assigned to athird resource instance, Server Z 904, although other relativeallocations could be used as well as should be apparent. By moving theinitial requests from the first resource instance 502, the system isable to provide the requested rate commitment using two resourceinstances instead of three.

As should be apparent, the rate commitment for a given user also candecrease for any of a number of similar reasons. Thus, at least some ofthe approaches used above to increase commitments can be usedsubstantially in reverse to decrease rate commitments. For example, inFIG. 6 where the user has 200 IOPS split evenly over two resourceinstances, if the user rate decreases to 100 IOPS then the system couldselect either instance to retain the 100 IOPS commitment and allow theother to release the commitment. If the rate falls to a level greaterthan 100 IOPS available on one of the servers, such as a rate of 150IOPS, the system could leave 100 IOPS on one server and either leave theother 50 IOPS on the current second server, or move those IOPS to athird server with about 50 IOPS on that server, in order to more fullyutilize the third server and increase the available capacity on thesecond server.

In the situation of FIG. 9, the user moved from 100 IOPS on Server X to400 IOPS on Server Y and 200 IOPS on server Z. If the user moved back to200 IOPS or 400 IOPS, the system could simply utilize the server thatalready has that amount allocated to the customer, and release thecommitment on the other server. If the user went down to 100 IOPS, thesystem could reduce the allocation on either Server Y or Z to 100 IOPS,or could move the customer back to Server X, if Server X still has 100IOPS available, in order to maximize the usage of Server X and maximizethe available capacity on Servers Y and Z. In other cases, the systemmight decide to move the customer to yet another server (not shown) thathas a capacity that most closely matches the desired level of IOPS.

In addition to moving, consolidating, or otherwise managing existingresources when adjusting capacity, systems and methods in accordancewith various embodiments can also monitor changes in available resourcesand update resource allocation in response to these changes. Forexample, FIG. 10 illustrates an example allocation 1000 wherein acustomer has a committed rate of 400 IOPS. The committed rate isprovided using three different servers 1002, 1004, 1006. In someembodiments, the system can detect when a resource instance becomesavailable, such as Server Z 1008, which is shown to have a committablecapacity of 400 IOPS. Instead of allocating new customer requests to thenewly available resource instance, the system in certain embodiments cananalyze existing allocations to attempt to consolidate existingcustomers onto fewer devices and/or instances. In this example, it isdetermined that server Z 808 has 400 available IOPS, and that Customer Ahas a committed rate of 400 IOPS spread across three servers. In orderto consolidate as much as possible, the system could decide to utilizeServer Z to provide all 400 TOPS for customer A. Such an approach canhelp to lower the complexity of managing and mapping various resourcesinstances, etc., as discussed above.

The decision to consolidate a customer onto fewer devices can betriggered by any of a number of events. In some embodiments, the controlplane can communicate with each resource instance periodically in orderto determine when a change in available capacity, such thatconsolidation might be possible. In some embodiments, when there is areduction in commitments for a resource instance, such as when acustomer lowers a committed rate or no longer utilizes the resource, atask can be established in the job queue of the control environment tocheck the commitments in the Admin data store, or other location, todetermine if any consolidation is possible. A similar approach could beutilized whenever a new resource instance is provisioned in the dataenvironment, such that a new record would be stored in the controlenvironment, for example. Various other approaches can be used as well,such as to periodically analyze the commitment information stored in thecontrol environment to determine possible approaches to consolidation.In cases where a user only requires a temporary increase or decrease incommitments, however, the system might not decide to consolidate inorder to minimize the copying of data, mapping updates, etc. Thus,certain criteria (e.g., commitment usage, length of time at the currentcommitment level, etc.) can be utilized in various embodiments todetermine whether to consolidate the resources for any given user.

As discussed, differing commitment levels can be allocated and/or datavolumes migrated for any of a number of reasons within the scope of thevarious embodiments. For example, a customer might explicitly request achange in resource commitment, such as by sending a Web services requestto an appropriate API of a management system. A customer might alsocontact an administrator or other authorized user, who can submit such arequest on behalf of the customer.

In various embodiments, the adjustments can be made due at least in partto detected changes in any of a number of different aspects of theresources in the data plane, as well as the usage of those resources.For example, a particular resource instance might be in an overloadsituation for longer periods of time than are acceptable, such as mightbe based upon specified criteria or thresholds. In such a situation, thesystem can decide to move at least one customer to a different instance,in order to reduce the average load on the often overloaded resourceinstance. In other embodiments, a customer might frequently exceed thecommitted rate, such that the system might decide to migrate the datavolume for that customer to a resource with greater capacity.

In some embodiments, the system might automatically adjust rates orother resource commitments for various users. For example, a customermight be willing to pay for different levels of commitments at differenttimes, but might not want to pay for the highest commitment rate whenthe customer is not using much of the committed capacity. In one suchembodiment, a customer can select two or more levels, tiers, or othervalues that can be used for commitment rates at various times. Forexample, a customer might be willing to pay for a committed rate of upto 500 IOPS if the committed rate is being used at least 75% ofcapacity. If the usage is less than 75% for a period of time, thecommitted rate might drop to a lower value, such as a committed rate of350 IOPS. The rate might stay at 350 IOPS until either the usage dropsbelow 75% of the 350 IOPS for a period of time, at which time the ratemight adjust to 200 IOPS, or the usage increases to at least 110% of thecommitted rate for a period of time, at which time the committed ratemight adjust back to 500 IOPS. The periods of time necessary to increaseor decrease the committed rate might be different, as the customer mightfavor either having committed rates for requests as much as possible oronly paying for higher committed rates when absolutely necessary, forexample. Further, there can be any appropriate thresholds, number oftiers, possible rates, or other such values within the scope of thevarious embodiments.

In some embodiments, an increase in rate commitment can be tied to theprocessing performance of the I/O requests for a customer. For example,a customer with a specified commitment rate might not want to increasethe rate as long as the customer's I/O requests are being processed in atimely fashion. As discussed, excessive requests can be processed in atimely fashion as long as there is sufficient uncommitted capacity on aresource, or there is unused committed capacity. If the resource entersan overload situation, for example, the excess requests may not beprocessed in a timely fashion, and could be slowed down in order toattempt to recover from the excessive load. The customer can authorizethe system in such a situation to automatically increase the committedrate, on the same resource or a different resource, in order to ensurethat subsequent requests from the customer are processed in a timelyfashion. Similarly, the usage of various resources can be monitored suchthat if capacity exists, the customer can automatically drop down to alower committed rate as long as any excess requests will likely beprocessed without significant delay.

By providing commitments at varying granularities, a provider canprovide a number of different pricing schemes. For example, a user mightpay a certain amount for each committed IOPS, such as $0.30 perguaranteed IOPS, whether or not the user actually uses that amount.Thus, if a user purchases a commitment of 100 IOPS for a month, the userwould pay $30 regardless of the actual usage, as the user is paying forthe commitment. Various other pricing approaches can be used as well,such as various tiered pricing schemes. In other embodiments, a usermight pay a premium for a level of committed IOPS, but that amount mightbe offset by the amount of unused commitment that was utilized by otherusers. For example, a user might pay $30 for 100 IOPS for a month, butif on average other users utilized 25 of those committed IOPS allocatedto that customer, the customer might see a reduction such as $0.05 perIOPS, for a total monthly fee of $25. If the rate is adjusted during aspecific period of time, the charge to the customer can reflect thedifferent rates apportioned over that period.

As discussed, a customer might go over their committed amount as well.Various pricing approaches can be used for these extra IOPS within thescope of various embodiments.

In one embodiment, the customer is charged the same for the excess IOPSas any customer having un-committed IOPS (e.g., $0.10 per IOPS), and thecustomer requests are treated the same as these requests. In otherembodiments, the customer can select to pay extra per IOPS to be handledwith the other requests, but given priority over standard requests. Insome embodiments, a customer can pay a premium to have their excessrequests processed within the available committed resources of anothercustomer, such that the requests will be handled as a committed requestas long as at least one other customer on the resource is below theirlevel of commitment. While customers may want the ability to spikerequest rates if needed, in certain embodiments users might be capped ata certain level, whether to limit customer costs, ensure certain levelsof quality of service, or for other such reasons. The ability to exceedguaranteed levels can also be beneficial to customers who are scaling asystem or application, as the customer can determine areas of needwithout suffering significantly in quality of service.

FIG. 11 illustrates an example of an environment 1100 that can utilizeand/or take advantage of aspects in accordance with various embodiments.As will be appreciated, although a Web-based environment is used forpurposes of explanation, different environments may be used, asappropriate, to implement various embodiments. The environment 1100shown includes both a testing or development portion (or side) and aproduction portion. The production portion includes an electronic clientdevice 1102, which can include any appropriate device operable to sendand receive requests, messages, or information over an appropriatenetwork 1104 and convey information back to a user of the device.Examples of such client devices include personal computers, cell phones,handheld messaging devices, laptop computers, set-top boxes, personaldata assistants, electronic book readers, and the like. The network caninclude any appropriate network, including an intranet, the Internet, acellular network, a local area network, or any other such network orcombination thereof. Components used for such a system can depend atleast in part upon the type of network and/or environment selected.Protocols and components for communicating via such a network are wellknown and will not be discussed herein in detail. Communication over thenetwork can be enabled by wired or wireless connections, andcombinations thereof. In this example, the network includes theInternet, as the environment includes a Web server 1106 for receivingrequests and serving content in response thereto, although for othernetworks an alternative device serving a similar purpose could be usedas would be apparent to one of ordinary skill in the art.

The illustrative environment includes at least one application server1108 and a data store 1110. It should be understood that there can beseveral application servers, layers, or other elements, processes, orcomponents, which may be chained or otherwise configured, which caninteract to perform tasks such as obtaining data from an appropriatedata store. As used herein the term “data store” refers to any device orcombination of devices capable of storing, accessing, and retrievingdata, which may include any combination and number of data servers,databases, data storage devices, and data storage media, in anystandard, distributed, or clustered environment. The application servercan include any appropriate hardware and software for integrating withthe data store as needed to execute aspects of one or more applicationsfor the client device, handling a majority of the data access andbusiness logic for an application. The application server providesaccess control services in cooperation with the data store, and is ableto generate content such as text, graphics, audio, and/or video to betransferred to the user, which may be served to the user by the Webserver in the form of HTML, XML, or another appropriate structuredlanguage in this example. The handling of all requests and responses, aswell as the delivery of content between the client device 1102 and theapplication server 1108, can be handled by the Web server. It should beunderstood that the Web and application servers are not required and aremerely example components, as structured code discussed herein can beexecuted on any appropriate device or host machine as discussedelsewhere herein. Further, the environment can be architected in such away that a test automation framework can be provided as a service towhich a user or application can subscribe. A test automation frameworkcan be provided as an implementation of any of the various testingpatterns discussed herein, although various other implementations can beused as well, as discussed or suggested herein.

The environment also includes a development and/or testing side, whichincludes a user device 1118 allowing a user such as a developer, dataadministrator, or tester to access the system. The user device 1118 canbe any appropriate device or machine, such as is described above withrespect to the client device 1102. The environment also includes adevelopment server 1120, which functions similar to the applicationserver 1108 but typically runs code during development and testingbefore the code is deployed and executed on the production side and isaccessible to outside users, for example. In some embodiments, anapplication server can function as a development server, and separateproduction and testing storage may not be used.

The data store 1110 can include several separate data tables, databases,or other data storage mechanisms and media for storing data relating toa particular aspect. For example, the data store illustrated includesmechanisms for storing production data 1112 and user information 1116,which can be used to serve content for the production side. The datastore also is shown to include a mechanism for storing testing data1114, which can be used with the user information for the testing side.It should be understood that there can be many other aspects that mayneed to be stored in the data store, such as for page image informationand access right information, which can be stored in any of the abovelisted mechanisms as appropriate or in additional mechanisms in the datastore 1110. The data store 1110 is operable, through logic associatedtherewith, to receive instructions from the application server 1108 ordevelopment server 1120, and obtain, update, or otherwise process datain response thereto. In one example, a user might submit a searchrequest for a certain type of item. In this case, the data store mightaccess the user information to verify the identity of the user, and canaccess the catalog detail information to obtain information about itemsof that type. The information then can be returned to the user, such asin a results listing on a Web page that the user is able to view via abrowser on the user device 1102. Information for a particular item ofinterest can be viewed in a dedicated page or window of the browser.

Each server typically will include an operating system that providesexecutable program instructions for the general administration andoperation of that server, and typically will include a computer-readablemedium storing instructions that, when executed by a processor of theserver, allow the server to perform its intended functions. Suitableimplementations for the operating system and general functionality ofthe servers are known or commercially available, and are readilyimplemented by persons having ordinary skill in the art, particularly inlight of the disclosure herein.

The environment in one embodiment is a distributed computing environmentutilizing several computer systems and components that areinterconnected via communication links, using one or more computernetworks or direct connections. However, it will be appreciated by thoseof ordinary skill in the art that such a system could operate equallywell in a system having fewer or a greater number of components than areillustrated in FIG. 11. Thus, the depiction of the system 1100 in FIG.11 should be taken as being illustrative in nature, and not limiting tothe scope of the disclosure.

An environment such as that illustrated in FIG. 11 can be useful for aprovider such as an electronic marketplace, wherein multiple hosts mightbe used to perform tasks such as serving content, authenticating users,performing payment transactions, or performing any of a number of othersuch tasks. Some of these hosts may be configured to offer the samefunctionality, while other servers might be configured to perform atleast some different functions. The electronic environment in such casesmight include additional components and/or other arrangements, such asthose illustrated in the configuration 200 of FIG. 2, discussed indetail below.

As discussed above, the various embodiments can be implemented in a widevariety of operating environments, which in some cases can include oneor more user computers, computing devices, or processing devices whichcan be used to operate any of a number of applications. User or clientdevices can include any of a number of general purpose personalcomputers, such as desktop or laptop computers running a standardoperating system, as well as cellular, wireless, and handheld devicesrunning mobile software and capable of supporting a number of networkingand messaging protocols. Such a system also can include a number ofworkstations running any of a variety of commercially-availableoperating systems and other known applications for purposes such asdevelopment and database management. These devices also can includeother electronic devices, such as dummy terminals, thin-clients, gamingsystems, and other devices capable of communicating via a network.

Various aspects also can be implemented as part of at least one serviceor Web service, such as may be part of a service-oriented architecture.Services such as Web services can communicate using any appropriate typeof messaging, such as by using messages in extensible markup language(XML) format and exchanged using an appropriate protocol such as SOAP(derived from the “Simple Object Access Protocol”). Processes providedor executed by such services can be written in any appropriate language,such as the Web Services Description Language (WSDL). Using a languagesuch as WSDL allows for functionality such as the automated generationof client-side code in various SOAP frameworks.

Most embodiments utilize at least one network that would be familiar tothose skilled in the art for supporting communications using any of avariety of commercially-available protocols, such as TCP/IP, OSI, FTP,UPnP, NFS, CIFS, and AppleTalk. The network can be, for example, a localarea network, a wide-area network, a virtual private network, theInternet, an intranet, an extranet, a public switched telephone network,an infrared network, a wireless network, and any combination thereof.

In embodiments utilizing a Web server, the Web server can run any of avariety of server or mid-tier applications, including HTTP servers, FTPservers, CGI servers, data servers, Java servers, and businessapplication servers. The server(s) also may be capable of executingprograms or scripts in response requests from user devices, such as byexecuting one or more Web applications that may be implemented as one ormore scripts or programs written in any programming language, such asJava®, C, C# or C++, or any scripting language, such as Perl, Python, orTCL, as well as combinations thereof. The server(s) may also includedatabase servers, including without limitation those commerciallyavailable from Oracle®, Microsoft®, Sybase®, and IBM®.

The environment can include a variety of data stores and other memoryand storage media as discussed above. These can reside in a variety oflocations, such as on a storage medium local to (and/or resident in) oneor more of the computers or remote from any or all of the computersacross the network. In a particular set of embodiments, the informationmay reside in a storage-area network (“SAN”) familiar to those skilledin the art. Similarly, any necessary files for performing the functionsattributed to the computers, servers, or other network devices may bestored locally and/or remotely, as appropriate. Where a system includescomputerized devices, each such device can include hardware elementsthat may be electrically coupled via a bus, the elements including, forexample, at least one central processing unit (CPU), at least one inputdevice (e.g., a mouse, keyboard, controller, touch screen, or keypad),and at least one output device (e.g., a display device, printer, orspeaker). Such a system may also include one or more storage devices,such as disk drives, optical storage devices, and solid-state storagedevices such as random access memory (“RAM”) or read-only memory(“ROM”), as well as removable media devices, memory cards, flash cards,etc.

Such devices also can include a computer-readable storage media reader,a communications device (e.g., a modem, a network card (wireless orwired), an infrared communication device, etc.), and working memory asdescribed above. The computer-readable storage media reader can beconnected with, or configured to receive, a computer-readable storagemedium, representing remote, local, fixed, and/or removable storagedevices as well as storage media for temporarily and/or more permanentlycontaining, storing, transmitting, and retrieving computer-readableinformation. The system and various devices also typically will includea number of software applications, modules, services, or other elementslocated within at least one working memory device, including anoperating system and application programs, such as a client applicationor Web browser. It should be appreciated that alternate embodiments mayhave numerous variations from that described above. For example,customized hardware might also be used and/or particular elements mightbe implemented in hardware, software (including portable software, suchas applets), or both. Further, connection to other computing devicessuch as network input/output devices may be employed.

Storage media and computer readable media for containing code, orportions of code, can include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information such as computer readable instructions, data structures,program modules, or other data, including RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disk (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe a system device. Based on the disclosure and teachings providedherein, a person of ordinary skill in the art will appreciate other waysand/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the invention asset forth in the claims.

What is claimed is:
 1. A computer-implemented method of adjustingcommitted rates for customers of shared resources, comprising: receivinga request to adjust a committed rate of input/output operations persecond (IOPS) guaranteed to a customer in a data environment, whereinthe IOPS are executed using guaranteed server capacity, wherein aportion of the guaranteed server capacity that is unused by the customeris available to at least one other customer, the request capable ofspecifying an adjusted committed rate, the request being received as aWeb service request to at least one application programming interface(API); when the request relates to decreasing the committed rate ofIOPS: reducing an amount of the guaranteed server capacity for thecustomer; when the request relates to increasing the committed rate ofTOPS: committing at least an additional portion of server capacity tothe customer; and storing information for the adjusted committed rate toa non-transitory data store, wherein the adjusted committed request rateis capable of being supplied by a single determined instance of the typeof server or a plurality of determined instances of the type of server,each of the plurality of determined instances of the type of serverproviding at least a portion of the requested committed request rate,and wherein each determined instances of the type of server is capableof having additional users sharing the determined instance of the typeof server when request capacity for the determined instance of the typeof server allows for the additional users.
 2. The computer-implementedmethod of claim 1, further comprising: analyzing commitment informationfor a plurality of servers in the data environment as stored in amanagement data store.
 3. The computer-implemented method of claim 1,wherein if the data environment is unable to provide the adjustedcommitted rate, the request to adjust the committed rate of IOPS isdenied.
 4. A computer-implemented method of adjusting usage of sharedservers, comprising: receiving a request for an adjusted committedrequest rate guaranteed to a customer with respect to a type of server,the customer having a current committed request rate for servers of thetype of server, wherein a portion of a capacity of the servers that isguaranteed to the customer and unused by the customer is available to atleast one other customer, the request capable of specifying a committedrequest rate; when the adjusted committed request rate is less than thecurrent committed request rate, reduce the committed request rate for atleast one instance of the type of server for the customer; when therequest relates to increasing the committed request rate, commit atleast a portion of an available committable rate capacity of at leastone instance of the type of server to obtain the adjusted committedrequest rate; and storing information for the adjusted committed requestrate for the customer for use in managing a rate of request handling forthe customer, wherein the adjusted committed request rate is capable ofbeing supplied by a single determined instance of the type of server ora plurality of determined instances of the type of server, each of theplurality of determined instances of the type of server providing atleast a portion of the requested committed request rate, and whereineach determined instances of the type of server is capable of havingadditional users sharing the determined instance of the type of serverwhen request capacity for the determined instance of the type of serverallows for the additional users.
 5. The computer-implemented method ofclaim 4, wherein the request is received from the customer or from amanagement component monitoring a usage by the customer.
 6. Thecomputer-implemented method of claim 4, further comprising: sending amessage to the customer indicating whether the adjusted requestedcommitted request rate is in effect.
 7. The computer-implemented methodof claim 4, wherein reducing the committed request rate includesreducing a number of instances of the type of server providing thecommitted request rate for the customer when a fewer number of instancesof the type of server is available to provide the committed requestrate.
 8. The computer-implemented method of claim 4, wherein increasingor reducing the committed request rate includes moving at least onerequest handling commitment to a different instance of the type ofserver providing the committed request rate for the customer.
 9. Thecomputer-implemented method of claim 4, wherein the customer is able torequest an adjusted committed server rate that is substantiallyindependent of a capacity of any single instance of the type of server.10. The computer-implemented method of claim 4, wherein the committedrequest rate for a type of server is a committed request rate ofinput/output operations per second (IOPS) for a data server.
 11. Thecomputer-implemented method of claim 4, wherein each instance of thetype of server is capable of supporting committed request rates formultiple customers, and wherein each instance of the type of server iscapable of supporting requests for additional customers withoutcommitted request rates.
 12. The computer-implemented method of claim 4,wherein at least one instance of the type of server is configured toprocess requests for customers with uncommitted request rates using anuncommitted or unused portion of a capacity of the at least one instanceof the type of server, and wherein in an overload situation the requestsfor the customers with committed request rates are handled at a normalrate and the requests for the customers without committed request ratesare slowed down to overcome the overload situation.
 13. Thecomputer-implemented method of claim 4, wherein a customer with acommitted request rate is able to exceed the committed request rate, andwherein any request over the committed request rate being handled at arate for requests without rate commitments or at a blended rate betweenrates for requests with and without rate commitments.
 14. Thecomputer-implemented method of claim 4, wherein determining an availablecommittable request capacity of at least one instance of the type ofserver includes randomly contacting instances of the type of server forat least one of capacity or commitment information.
 15. Thecomputer-implemented method of claim 4, further comprising: charging thecustomer based at least in part on the adjusted committed request ratewith respect to the type of server for the customer.
 16. Acomputer-implemented method of adjusting usage of shared servers,comprising: receiving a request for an adjusted committed rate ofinput/output operations per second (IOPS) guaranteed to a customer withrespect to a type of server, wherein the IOPS are executed using serversof the type, wherein a portion of a capacity of the servers that isguaranteed to the customer and unused by the customer is available to atleast one other customer, the customer having a current committed rate,the request capable of specifying an adjusted committed rate; when theadjusted committed rate of IOPS is less than the current committed rate,reduce the committed rate for at least one instance of the type ofserver for the customer; when the request for an adjusted committed rateof IOPS relates to increasing the committed rate, commit at least aportion of an available committable rate capacity of at least oneinstance of the type of server to obtain the adjusted committed rate;and storing information for the adjusted committed rate for the customerfor use in managing a rate of IOPS for the customer, wherein theadjusted committed request rate is capable of being supplied by a singledetermined instance of the type of server or a plurality of determinedinstances of the type of server, each of the plurality of determinedinstances of the type of server providing at least a portion of therequested committed request rate, and wherein each determined instancesof the type of server is capable of having additional users sharing thedetermined instance of the type of server when request capacity for thedetermined instance of the type of server allows for the additionalusers.
 17. The computer-implemented method of claim 16, wherein at leastone instance of the type of server is configured to process requests forcustomers with uncommitted rates using an uncommitted or unused portionof a capacity of the at least one instance of the type of server, andwherein in an overload situation the requests for the customers withcommitted rates are handled at a normal rate and the requests for thecustomers without committed rates are slowed down to overcome theoverload situation.
 18. The computer-implemented method of claim 16,wherein a customer with a committed rate is able to exceed the committedrate, and wherein any request over the committed rate being handled at arate for requests without rate commitments or at a blended rate betweenrates for requests with and without rate commitments.
 19. A system foradjusting usage of a shared server, comprising: at least one processor;and memory including instructions that, when executed by the at leastone processor, cause the system to: receive a request for an adjustedcommitted rate guaranteed to a customer with respect to a type ofserver, the customer having a current committed rate for the type ofserver, wherein a portion of a capacity of the server that is unused bythe customer is available to at least one other customer, the requestcapable of specifying a committed rate corresponding to any portion of acapacity of one or more instances of the type of server; when theadjusted committed rate is less than the current committed rate, reducethe committed rate for at least one instance of the type of server forthe customer; when the request relates to increasing the committed rate,commit at least a portion of an available committable rate capacity ofat least one instance of the type of server to obtain the adjustedcommitted rate, and store information for the adjusted committed ratefor the customer for use in managing a rate of request handling for thecustomer, wherein the adjusted committed request rate is capable ofbeing supplied by a single determined instance of the type of server ora plurality of determined instances of the type of server, each of theplurality of determined instances of the type of server providing atleast a portion of the requested committed request rate, and whereineach determined instances of the type of server is capable of havingadditional users sharing the determined instance of the type of serverwhen request capacity for the determined instance of the type of serverallows for the additional users.
 20. The system of claim 19, wherein therequest is received from the customer or from a management componentmonitoring a usage by the customer.
 21. The system of claim 19, whereinreducing the committed rate includes reducing a number of instances ofthe type of server providing the committed rate for the customer when afewer number of instances of the type of server is available to providethe committed rate, and wherein increasing or reducing the committedrate includes move at least one usage commitment to a different instanceof the type of server providing the committed rate for the customer. 22.The system of claim 19, wherein the committed rate for a type of serveris a committed rate of input/output operations per second (TOPS) for adata server.
 23. A non-transitory computer-readable storage mediumincluding instructions for adjusting usage of a shared server, theinstructions when executed by a processor causing the processor to:receive a request for an adjusted committed rate guaranteed to acustomer with respect to a type of server, wherein a portion of acapacity of the servers that is guaranteed to the customer and unused bythe customer is available to at least one other customer, the customerhaving a current committed rate for the type of server, the requestcapable of specifying a committed rate corresponding to any portion of acapacity of one or more instances of the type of server; if the adjustedcommitted rate is less than the current committed rate, reduce thecommitted rate for at least one instance of the type of server for thecustomer; if the request relates to increasing the committed rate,commit at least a portion of an available committable rate capacity ofat least one instance of the type of server to obtain the adjustedcommitted rate; and store information for the adjusted committed ratefor the customer for use in managing a rate of request handling for thecustomer, wherein the adjusted committed request rate is capable ofbeing supplied by a single determined instance of the type of server ora plurality of determined instances of the type of server, each of theplurality of determined instances of the type of server providing atleast a portion of the requested committed request rate, and whereineach determined instances of the type of server is capable of havingadditional users sharing the determined instance of the type of serverwhen request capacity for the determined instance of the type of serverallows for the additional users.
 24. The non-transitorycomputer-readable storage medium of claim 23, wherein the request isreceived from the customer or from a management component monitoring ausage by the customer.
 25. The non-transitory computer-readable storagemedium of claim 23, wherein reducing the committed rate includesreducing a number of instances of the type of server providing thecommitted rate for the customer when a fewer number of instances of thetype of server is available to provide the committed rate, and whereinincreasing or reducing the committed rate includes move at least onecommitment to a different instance of the type of server providing thecommitted rate for the customer.
 26. The non-transitorycomputer-readable storage medium of claim 23, wherein the committed ratefor a type of server is a committed rate of input/output operations persecond (IOPS).
 27. The non-transitory computer-readable storage mediumof claim 23, wherein the type of server is a physical server or avirtual server.